Nonlinear stochastic filtering technique for radar/lidar inversion

Jose M. B. Dias; Elsa S. R. Fonseca

doi:10.1117/12.364048

4 October 1999 Nonlinear stochastic filtering technique for radar/lidar inversion

Jose M. B. Dias, Elsa S. R. Fonseca

Proceedings Volume 3809, Signal and Data Processing of Small Targets 1999; (1999) https://doi.org/10.1117/12.364048
Event: SPIE's International Symposium on Optical Science, Engineering, and Instrumentation, 1999, Denver, CO, United States

Abstract

This paper addresses the joint estimation of backscatter and extinction coefficients from range/time noisy data under a nonlinear stochastic filtering setup. This problem is representative of many remote sensing applications such as weather radar and elastic-backscatter lidar. A Bayesian perspective is adopted. Thus, in addition to the observation mechanism, relating in a probabilistic sense the observed data with the parameters to be estimated, a prior probability density function has to be specified. We adopt as prior a causal first order auto-regressive Gauss-Markov random field. By using a reduced order state-space representation of the prior, we derive a nonlinear stochastic filter that recursively computes the backscatter and extinction coefficients at each site. A set of experiments based on simulated data illustrates the potential of the proposed approach.

Citation Download Citation

Jose M. B. Dias and Elsa S. R. Fonseca "Nonlinear stochastic filtering technique for radar/lidar inversion", Proc. SPIE 3809, Signal and Data Processing of Small Targets 1999, (4 October 1999); https://doi.org/10.1117/12.364048

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